noharm.ai: Enhancing Patient Safety in Clinical Pharmacy

noharm.ai is a cutting-edge AI-powered SaaS platform designed for hospitals and clinical pharmacies to improve patient safety and care quality through intelligent prescription analysis. Built in collaboration with leading healthcare institutions in Brazil, it leverages natural language processing to detect risks such as drug interactions, duplications, incompatibilities, and non-standard prescribing practices, while providing real-time alerts and prioritized risk screening. The system supports decision-making with patient risk stratification using severity scores, interactive real-time graphics, and comprehensive management reports on key performance indicators. With proven impact across 149+ healthcare units and over 30 million in savings, noharm.ai integrates seamlessly into hospital data systems to streamline pharmacotherapy and reduce adverse events.

Key Features:

• AI-powered prescription risk analysis using natural language processing
• Real-time alerts for drug interactions, duplications, incompatibilities, and cross-reactivity
• Detection of non-standard prescriptions based on dose, frequency, route, and controlled substance criteria
• Prioritization screen for sorting prescriptions by risk indicators (e.g., altered lab exams, maximum dose)
• Patient risk stratification with severity scoring and real-time visual analytics
• Comprehensive reporting on Clinical Pharmacy KPIs: prescriptions screened, interventions made, acceptance rates
• Integration with hospital data systems to enhance efficiency and care quality
• Support for pharmacotherapy monitoring and fostering a patient safety culture

Pricing: noharm.ai operates on a subscription model with pricing based on the number of beds (both private and public) in the healthcare facility, including integration and monthly fees.

Conclusion: noharm.ai is a transformative solution for clinical pharmacy, combining advanced AI with real-world hospital collaboration to significantly improve medication safety, reduce errors, and drive measurable healthcare outcomes.